A survey conducted by a research team was to investigate how education level, tenure in current employment, and age are related to annual income. A sample of 20 employees was selected and the same data as in the previous problem were collected. In addition, a multiple linear regression analysis was performed to predict annual income from the other 3 variables. A portion of the output from the analysis is shown below.

	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%
Intercept	-143481.19	39925.60	-3.59	0.00	-228119.67	-58842.71
Education	10011.92	2570.58	3.89	0.00	4562.52	15461.32
Length of tenure	-2193.88	2158.83	-1.02	0.32	-6770.40	2382.63
Age	2689.24	986.35	2.73	0.01	598.26	4780.22

a. All other things being equal, if an employee's length of tenure in their current employment increased by one year, how much would we predict their annual income would change? Enter your answer as an integer. If you predict that annual income will decrease, enter a negative sign before your number. Do not enter a dollar sign in the box.

b. All other things being equal, if an employee's age increased by one year, how much would we predict their annual income would change? Enter your answer as an integer. If you predict that annual income will decrease, enter a negative sign before your number. Do not enter a dollar sign in the box.

c. What do you predict annual income would be for a 44-year old employee with 13 years of education and 18 years of tenure in their current employment? Enter your answer as an integer. Do not enter a dollar sign in the box.